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Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)
0.13
Performance library for Deep Learning
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Memory descriptor. More...
#include <mkldnn_types.h>

Public Attributes | |
| mkldnn_primitive_kind_t | primitive_kind |
| The kind of primitive. More... | |
| int | ndims |
| Number of dimensions. More... | |
| mkldnn_dims_t | dims |
| Dimensions in the following order: mini-batch, channel, spatial. More... | |
| mkldnn_data_type_t | data_type |
| Data type of the tensor elements. More... | |
| mkldnn_memory_format_t | format |
| Memory format. More... | |
| union { | |
| mkldnn_blocking_desc_t blocking | |
| Description of the data layout for memory formats that use blocking. More... | |
| } | layout_desc |
Memory descriptor.
The description is based on a number of dimensions, dimensions themselves, plus information about elements type and memory format. Additionally, contains format-specific descriptions of the data layout.
| mkldnn_blocking_desc_t mkldnn_memory_desc_t::blocking |
Description of the data layout for memory formats that use blocking.
| mkldnn_data_type_t mkldnn_memory_desc_t::data_type |
Data type of the tensor elements.
| mkldnn_dims_t mkldnn_memory_desc_t::dims |
Dimensions in the following order: mini-batch, channel, spatial.
For example: {N, C, H, W}.
| mkldnn_memory_format_t mkldnn_memory_desc_t::format |
Memory format.
| union { ... } mkldnn_memory_desc_t::layout_desc |
| int mkldnn_memory_desc_t::ndims |
Number of dimensions.
| mkldnn_primitive_kind_t mkldnn_memory_desc_t::primitive_kind |
The kind of primitive.
Used for self identifying the primitive descriptor. Must be mkldnn_memory.
1.8.13